Costs of operation & maintenance, assembly, transport and installation of offshore wind turbines contribute significantly to the total cost of offshore wind farm. These operations are mostly carried out by specific ships that have to be hired for the operational phase and for duration of installation process, respectively. Duration, and therefore ship hiring costs is, among others, driven by waiting time for weather windows for weather-sensitive operations. Today, state of the art decision making criteria for weather-sensitive operations are restrictions to the significant wave height and the average wind velocity at reference height. However, actual limitations are physical, related to response of equipment used e.g. crane wire tension, rotor assembly motions while lifting, etc. Transition from weather condition limits to limits on physical equipment response in decision making would improve weather window predictions, potentially reducing cost of offshore wind energy. This paper presents a novel approach to weather window estimation using ensemble weather forecasts and statistical analysis of simulated installation equipment response.
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